1. Field of the Invention
The present invention relates to language translation resources configured for translating Instant Messages (IM) that are sent from a sending user to a receiving user.
2. Description of the Related Art
Computer-based language translation resources enable a user to translate a document or message from one language into another message. These translation resources rely on a user of a client device to initiate the translation. Hence, manual intervention is required by a client device to request translation of a document.
This requirement of manual intervention for translation also exists with instant messaging applications. One exemplary translation resource is the commercially-available “IM Translator for IE” (available from Smart Link Corporation at the Internet website “imtranslator.net/plugin-tr.asp”), which is an executable plug-in resource for the Microsoft Internet Explorer 5.5/6.x web browser that provides multilingual capabilities for Internet Explorer. Hence, this plug-in resource is implemented in the client device and executed in response to manual intervention by the user. Other exemplary translation resources executed in a client device include the commercially available “SDLChat Translator” (available from SDL International at the Internet website “freetranslation.com”), where a user initiates an executable instance of the translation resource and performs a manual assignment (i.e., association) of the translation resource instance with an instance of the instant messaging resource (i.e., the instant messaging window).
Translation software that is initiated in response to a user request also may reside on a server, for example in the form of web-based translation services such as the “Language Tools” web site offered by Google Corporation at the Internet web site “google.com/language_tools”.
More advanced translation services are being integrated into instant messaging services, where a user sending an instant message may include with the message a request for the instant message to be translated using a servlet at the instant messaging server. For example, the commercially available IBM Workplace Instant Messaging Service Provider Interface (SPI) enables a user to request a translation servlet for translating instant messages as they are sent by the user. However, the translation servlet described by the IBM Workplace Instant Messaging SPI for language translation still requires the user to initiate the translation servlet.
Hence, the foregoing translation techniques require a user to manually request translation in order to enable translation of an instant message. Such techniques are inconvenient for destination parties receiving the instant messages, since the destination parties do not have any way for implementing automatic translation of the instant message without first notifying the sending party. Such notification may be impossible if the destination party does not know the language used by the sending party at all.
Another fundamental concern regarding computer-based language translation resources is that the quality of the translation will never be as good as a human translation, because a human translator is able to provide a more effective translation based on a thorough evaluation of the context of message content that is presented to the human translator by the message sender (i.e., source). For example, a human translator can evaluate the context of the content of a message based not only on message text (assuming the message is written), but also based on non-text attributes. Exemplary non-text attributes may include attributes of the message sender, such as the writer's profession which may affect the technical vocabulary (e.g., medical terms vs. engineering terms vs. legal terms), location of the message sender (which may reflect location-specific vernacular terms or expressions), age of the sender or time and/or date the message is sent (reflecting temporal-based or time-based vernacular terms or expressions), or if the message is spoken, then the inflection or intonation of the speaker presenting the message.
As apparent from the foregoing, however, determining message context from inflection or intonation of spoken text is not yet possible for computer-based systems, and computer-based language translation resource have not yet developed the sophistication to provide translation based on non-text attributes (e.g., technical vocabulary, vernacular, etc.). Use of a human interpreter between to parties of an instant messaging session is not a practical alternative.